Brunobkr/llama.cpp_AlgMor24_github
ΩFFFΣLLIa • llama.cpp • AlgMor24 ██████╗ ███████╗███████╗███████╗██╗ ██╗ ██╗ █████╗ ██╔═══██╗██╔════╝██╔════╝██╔════╝██║ ██║ ██║██╔══██╗ ██║ ██║█████╗ █████╗ █████╗ ██║ ██║ ██║███████║ ██║ ██║██╔══╝ ██╔══╝ ██╔══╝ ██║ ██║ ██║██╔══██║ ╚██████╔╝██║ ██║ ███████╗███████╗███████╗██║██║ ██║ ╚═════╝ ╚═╝ ╚═╝ ╚══════╝╚══════╝╚══════╝╚═╝╚═╝ ╚═╝ High-Performance LLM / VLM Inference & Autonomous Agentic Ecosystem… See the full description on the dataset page: https://huggingface.co/datasets/Brunobkr/llama.cpp_AlgMor24_github.
03.1k
1#version 4502 3#include "soft_max_large_common.glsl"4 5void main() {6 const uint tid = gl_LocalInvocationID.x;7 const uint rowx = gl_WorkGroupID.y;8 const uint wg_start = gl_WorkGroupID.x * BLOCK_SIZE * num_iters;9 10 const uint32_t i03 = rowx / (p.ne01 * p.ne02);11 const uint32_t i02 = (rowx - i03 * p.ne01 * p.ne02) / p.ne01;12 const uint32_t i01 = rowx % p.ne01;13 14 uint rowy_start = 0;15 if (p.KY > 0) {16 rowy_start = i01 * p.nb11 + (i02 % p.ne12) * p.nb12 + (i03 % p.ne13) * p.nb13;17 }18 19 if (rowx >= p.nrows_x) {20 return;21 }22 23 float slope = get_slope(rowx);24 25 // Find max26 FLOAT_TYPE max_val = p.has_sinks == 0 ? uintBitsToFloat(0xFF800000) : data_c[i02];27 28 [[unroll]] for (uint i = 0; i < gl_NumWorkGroups.x; i += BLOCK_SIZE) {29 if (i + tid < gl_NumWorkGroups.x) {30 max_val = max(max_val, data_m[rowx * gl_NumWorkGroups.x + i + tid]);31 }32 }33 34 // reduce across the workgroup35 vals[tid] = max_val;36 barrier();37 [[unroll]] for (uint s = BLOCK_SIZE / 2; s > 0; s >>= 1) {38 if (tid < s) {39 vals[tid] = max(max_val, vals[tid + s]);40 }41 barrier();42 }43 44 max_val = vals[0];45 barrier();46 47 FLOAT_TYPE sum = FLOAT_TYPE(0.0f);48 49 // Compute sum{exp(x - max)}50 [[unroll]] for (uint col0 = wg_start, idx = 0; idx < num_iters; col0 += BLOCK_SIZE, ++idx) {51 const uint col = col0 + tid;52 53 if (col >= p.KX) {54 break;55 }56 57 // compute exp(a*scale+b*slope), add it to sum58 const uint i = rowx * p.KX + col;59 FLOAT_TYPE val;60 val = exp(FLOAT_TYPE(data_a[i]) * p.scale + (p.KY > 0 ? slope * FLOAT_TYPE(data_b[rowy_start + col]) : FLOAT_TYPE(0.0f)) - max_val);61 sum += val;62 data_d[i] = D_TYPE(val);63 }64 65 // reduce across the workgroup66 vals[tid] = sum;67 barrier();68 [[unroll]] for (uint s = BLOCK_SIZE / 2; s > 0; s >>= 1) {69 if (tid < s) {70 vals[tid] += vals[tid + s];71 }72 barrier();73 }74 75 if (tid == 0) {76 sum = vals[0];77 data_s[rowx * gl_NumWorkGroups.x + gl_WorkGroupID.x] = sum;78 }79}80 